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# ============================================================================
import torch
from torch import nn
import torch.nn.functional as F


class FusedLeakyReLU(nn.Module):
    def __init__(self, channel, negative_slope=0.2, scale=2 ** 0.5):
        super(FusedLeakyReLU, self).__init__()

        self.bias = nn.Parameter(torch.zeros(channel))
        self.negative_slope = negative_slope
        self.scale = scale

    def forward(self, x):
        return fused_leaky_relu(x, self.bias, self.negative_slope, self.scale)


def fused_leaky_relu(x, bias, negative_slope=0.2, scale=2 ** 0.5):
    return scale * F.leaky_relu(x + bias.view((1, -1)+(1,)*(len(input.shape)-2)), negative_slope=negative_slope)
